Forthcoming articles

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International Journal of Autonomous and Adaptive Communications Systems (22 papers in press)

Regular Issues

A Heuristic Approximation Algorithm for the Steiner Tree Based on Prior Multicast Nodesby Weijun Yang, Yun Zhang, Yuanfeng Chen, Jianqi Liu Abstract: Multicast routing is regarded as a critical component in networks, especially the real-time applications for multimedia become increasingly popular. Finding such a Steiner tree in multicast routing is an NP-complete problem as for as we know. This paper devises a novel and improved prior nodes minimum cost path heuristic approximation algorithm (IPNMPH) to deal with it. Some paths passing through adjusted prior destination nodes are selected, and they partly share links in the network and decrease the cost of the multicast routing tree. The theoretical validations for the proposed algorithm show that its approximation ratio is 2(1-1/q) and the time complexity is O(nKeywords: multicast routing; Steiner tree; approximation algorithm; prior nodes;.

Community outlier detection in social networks based on graph matchingby Soufiana Mekouar, Nabila Zrira, El Houssine Bouyakhf Abstract: Outlier or anomaly detection is widely used in several fields of study such as statistics, data mining, and social networks. It can reveal important anomalous and interesting outlier behaviors in the social network communities. In this work, we propose a new approach for community outlier detection based on social network graph matching. We identify community structures in social networks using some community detection methods. For each community, the node signature is combined with an optimal assignment method for matching the original graph data with the graph pattern data, in order to detect two formalized anomalies: anomalous nodes and anomalous edges. We also define a distance between two graphs using Euclidean formula. Then, we define a node-to-node cost in an assignment problem using the Hungarian method to deduce the matching function. The obtained experimental results demonstrate that our approach performs on real social network datasets.Keywords: Community outlier detection; node signature; Hungarian method; graph matching.

A Minimum Knapsack based Resource Allocation for Underlaying Device-to-Device Communicationby Mohammad Islam, Abd-Elhamid Taha, Selim Akl Abstract: As the numbers of devices are increasing, the proximity based services have enabled Device-to-Device (D2D) communication to be regarded as one of the major communication paradigms. In underlaying D2D, the devices communicating with each other directly use shared cellular resources. In this paper we propose a MInimum Knapsack based Interference aware Resource Allocationrnalgorithm (MIKIRA) for D2D communication underlaying cellular networks.rnWe compare the system sum rates, interference and Signal-to-Interference-and-Noise-Ratios (SINR) of MIKIRA with a Graph based Resource Allocation (GRA) algorithm and random allocation. In our three different sets of experiments with different percentages of D2D pairs in the total number of cellular users in the network we observe that, MIKIRA performs better than the other algorithms in terms of interference and SINR, and obtains similar system sum rate. MIKIRA (O(n^2 log(n))) is also computationally more efficient when compared with the GRA (O(n^3)), which makes it suitable for use in LTE scheduling period of 1 ms.Keywords: Resource Allocation; Minimum Knapsack; Device-to-Device; Cellular Networks; Underlaying; Spectrum Sharing.

Wireless Standard Technology Identification via Signal Temporal Characteristics: A Comprehensive 802.11b/g/n Case Studyby Samer Rajab, Walid Balid, Hazem Refai, Mohamad Al Kalaa Abstract: ISM spectrum is becoming increasingly populated with various wireless technologies that may or may not utilize similar rules for sharing the spectrum. Consequently, wireless coexistence suffers especially when heterogeneous communicating wireless devices are collocated and sharing the same spectrum. Technology awareness of the collocated devices will provide a pathway to improving wireless coexistence. This paper presents a novel method for identifying wireless technologies through the use of simple energy detection techniques to measure channel temporal characteristics including activity and idle time probability distributions. First, time distributions belonging to a particular 802.11 standards are obtained via experimental measurements. Then, features uniquely belonging to specific wireless technologies are extracted from their corresponding temporal distributions and fed into a machine-learning algorithm to identify the technologies under evaluation. Wireless technology identification enables situational awareness to improve coexistence and reduce interference among the devices. An intelligent wireless device is capable of detecting wireless technologies operating in the vicinity. This can be performed by scanning energy levels without the need for signal demodulation and decoding. In this work, a wireless technology identification algorithm was assessed experimentally. Temporal traffic pattern for 802.11b/g/n homogeneous and heterogeneous networks were measured and used as algorithm input. Identification accuracies of up to 96.83% and 85.9% were achieved for homogeneous and heterogeneous networks, respectively.Keywords: wireless technology identification; wireless coexistence; cognitive radio; energy detection; machine learning.

An Energy-Aware Clustering Algorithm for Wireless Sensor Networks: GA based Approachby Payal Khurana Batra, Krishna Kant Abstract: Energy conservation is the predominant requirement of wireless sensor
networks. Clustering is a technique which helps in achieving the goal of energy
efficiency and scalability. Several clustering approaches using Genetic Algorithm
(GA) as an optimization tool are proposed in the literature. Most of these clustering
approaches lead to multi-objective optimization. In this paper, we propose a GA
based Clustering Algorithm (GACA) which considers major factors responsible
for effective clustering. The proposed approach has been compared with existing
approaches for the best fit and optimal fit case. Simulation results show that the
proposed GACA approach is more energy efficient than existing approaches and
optimal fit results are better than the best fit results.
Keywords: clustering; network lifetime; energy efficiency; genetic algorithm;
wireless sensor networks.

A novel adaptation approach for collaborative ubiquitous applicationsby Imen Abdennadher, Ismael Bouassida Rodriguez, Mohamed Jmaiel Abstract: Ubiquitous computing environments provide a wide range of challenges and possibilities in distributed systems. Ubiquitous communicating systems have particular characteristics, such as their dynamic nature and the great number of users and heterogeneous devices involved. The problem of adapting collaborative applications on top of ubiquitous communicating systems is an important issue. In our view, solutions for such applications adaptation must ensure the selection of the most suitable architectural configuration according to context while respecting users'requirements. In this paper, we present a novel adaptation approach and a description of its use in the context of the Smart Building case study. We address the adaptation of the Smart Building Application on two levels. The high-level adaptation aims to reduce the energy consumption of the building while respecting the comfort of users. The low-level adaptation is related to the software architecture of the application. In this level, a new deployment of the software components is generated according to resources context parameters and a decision policy called "Disorder Increase". The implementation of this decision policy has been evaluated. We show that the "Disorder Increase" can effectively make the selection of the most suitable architectural configuration easier and more efficient than other decision policies.Keywords: Ubiquitous Collaborative Systems; adaptation; decision policies; Smart Building; energy consumption.

MultipathP2P: A Simple Multipath Ant Routing System for P2P Networksby Mohamed Amine RIAHLA, Karim Tamine Abstract: This paper presents MultPathP2P that is a new routing protocol dedicated to P2P system. MultPathP2P relies on the social networks concepts where nodes are identified through their virtual addresses. The proposed protocol will decrease the routing overhead within the network. The main idea consist of using Mobile Agents in order to find optimal routes towards the destination nodes. These Agents are generated by each network node. Whenever a network node plans to request a resource in the network, it set a local resource request rather than broadcasting it. Then, this request will be shared among the others nodes using the Agents which are moving within the network. We also present a data routing protocol based on ants general behavior in order to increase the performance of MultiPathP2P. The Simulation results show that our new algorithm provide a significant improvement in terms of various performance metrics compared to other protocols.Keywords: Swarm intelligence; Mobile Multi Agent Systems; P2P networks; routing protocol.

Game theory approach to peer-to-peer video streaming: a comprehensive surveyby Hamidreza Mahini, Mehdi Dehghan, Hamidreza Navidi, Amir Masoud Rahmani Abstract: Recent reports and forecasts indicate video is the most important part of the Internet traffic. This traffic is the result of increasing video applications, also the high expectations of today users. In fact, streaming HD videos with minimum initial buffering time and interrupting forms the QoE backbone. Therefore, resource provisioning for this demands is very challenging and the scalability of these systems depends on spending a high cost on preparation new resources or taking the advantage of users abilities in the form of a peer-to-peer (p2p) system. Although p2p architecture can significantly improve scalability but it has severe management complexity challenges. The dynamic nature and the autonomy of peers are the prominentreasonsfor this issue. Because of the strategic context in p2p video streaming and due to the existence of conflicting actions for participant entities in such systems, using game theory has been very interesting as a mathematical tool for modeling and analyzing in recent related investigations. Due to the multitude of these methods, the lack of a comprehensive review is intensively palpable. This paper seeks to fill this research gap especially with focus on applying non-cooperative games to p2p video streaming resource allocation.Keywords: Peer-to-Peer; Video Streaming; Game Theory.

Biologically Inspired Modeling of Smart Grid for Dynamic Power-Flow Control under Power Failureby Hidefumi Sawai, Hideaki Suzuki, Hiroyuki Ohsaki Abstract: Smart grid is an electric power network that enables an eﬀective use of electric power in a highly parallel distributed manner. We have ﬁrst formulated the basic equations for the smart grid by inspiring from the mechanisms in biological organism, and controled the power-ﬂow dynamically in the smart grid by monitoring an objective function, which reﬂects the power-ﬂow and the constraint imposing on the power nodes. To validate the operation of the smart grid, we performed several simulation experiments, which include the operations of a conventional power network, a microgrid (comprises eight power nodes), and a smart grid (comprises three microgrids integrated into the conventional power network) both in synchronous and asynchronous manners for the operation of power nodes. Furthermore, even for several cases of power failure such as outage, a thunderbolt shock on the power plant and disconnection of power cables, power recovery can be automatically achieved through bypass connections similar to synaptic interconnections in a dynamic function of brain. Thus, the proposed control method guarantees a dynamically stable operation even in several cases of power failure by monitoring the objective function, while always reﬂecting an optimal state in smart grid as a whole system.Keywords: smart grid; dynamic power-flow control; highly distributed asynchronous system; brain function; fault tolerance.

Research on offshore wind power monitor based on wireless satellite communication systemby Xilong Qu, Hui Yu, Aofeng Zhang Abstract: Satellite communication and combination communication of is the new development direction of mobile communications, and the important supplement of the mobile communication as well. The basic theory of transmission and the whole mobile satellite communications system is introduced in details, and the various parts of the system functions about the space station and earth stations are presented. Satellite channels including Nakagami fading channel, Suzuki model, Corraza models and C. Loo model are analyzed and compared, and comparative results are analyzed in depth. Moreover, the importance of offshore wind power monitor is presented, and the use of satellite communications method for offshore wind monitoring unit is a feasible and effective solution. It has profound theoretical significance for the development of wireless satellite communications.Keywords: mobile satellite communication system; link design; offshore wind power ; channel model simulation; wireless satellite communication.

B-DASH: Broadcast-based Dynamic Adaptive Streaming over HTTPby KOFFKA KHAN, Wayne Goodridge Abstract: Multiple video players competing at a bottleneck link give rise to overlapping ON-OFF traffic patterns. These patterns may introduce the problem of overlapping oscillatory effects amongst players resulting in poor video quality, frequent flickering and video freezes. We propose a distributed heuristic hybrid-based approach called B-DASH to address this problem. B-DASH implements two mechanisms: (1) message exchange and (2) adaptation. During message exchange, a broadcast mechanism is used to send information to neighboring players. Based on the information present in this exchange, players can adapt to different network conditions. In this adaptation approach, B-DASH players with the higher estimated bandwidth are forced to reduce their bitrate request, while players with the lowest estimated bandwidth increase their bitrate request. This action reduces the oscillatory effects of the ON-OFF traffic patterns. Adaptive video streaming players using the B-DASH approach are compared to other players using Conventional, PANDA and ELASTIC approaches. Experimental evaluation of B-DASH indicates good quality of experience (QoE) characteristics for players. Possible trade-offs for players using the B-DASH approach are investigated under various network conditions. The results show improvements of up to 5% bandwidth utilization, 79% fairness, 27% re-buffering ratios, 57% stability and 9% quality.Keywords: ON-OFF traffic; oscillatory; quality; flickering; freezes; distributed; heuristic; B-DASH; bitrate requests; QoE; fairness; stability.

Chaotic discrete bat algorithm for capacitated vehicle routing problemby Yanguang Cai, Yuanhang Qi, Hao Cai, Helie Huang, Houren Chen Abstract: This paper presents a chaotic discrete bat algorithm for addressing the capacitated vehicle routing problem. The proposed algorithm presents new parameters and operations for the bat algorithm, and uses a penalty function method to address the constraint conditions. The proposed algorithm also introduces a chaotic initialization for bat populations, and adopts a local search strategy which is combined with a 2-Opt strategy, insert strategy and exchange strategy to expand the local search space. Experimental results show that: the proposed algorithm is better than alternative algorithms in terms of optimization capability, robustness and time consumption, and there are significant differences between the proposed algorithm and alternative algorithms.Keywords: Discrete Bat Algorithm; Chaotic Optimization Algorithm; Capacitated Vehicle Routing Problem; Vehicle Routing Problem.

Power load clustering algorithm for demand responseby Yanguang Cai, Helie Huang, Hao Cai, Yuanhang Qi Abstract: Satisfactory clustering of power load is an essential prerequisite for the effective implementation of demand response (DR) programs. Focusing on the inability of commonly used clustering algorithms to specify the similarity degree between load profiles, this paper proposes a novel power load similarity measurement criterion based on the maximum deviation, similarity degree and deviation degree, termed Maximum Deviation Similarity Criterion (MDSC). We further propose a power load clustering algorithm based on the MDSC for obtaining reasonable load classification. The proposed MDSC is capable of specifying the similarity degree and effectively describes the shape similarity between load profiles. Furthermore, the criterion is simple, reasonable and flexible in nature. A case study with 32 load data clustering analysis is used to verify the proposed clustering algorithm. Experimental results demonstrate that the proposed clustering algorithm is computationally faster and has a better clustering efficiency, allowing it to better meet the needs of DR programs.Keywords: demand response; power load; shape similarity; maximum deviation similarity criterion; clustering algorithm.

Towards Cognitive Radio Based eHealth Systemsby Dramane Ouattara, Mohamed Aymen Chalouf, Francine Krief Abstract: In this paper, we investigate the use of intelligent communicationrnsystems (cognitive radio) in medical data transmission process. Therefore,rnbased on the work in progress (state of the art), we propose a more completerncognitive radio communication architecture in eHealth systems. The goal isrnto determine the different contexts related to patient monitoring and point outrnsome significant technical challenges required for more flexible and effectiverntransmissions. Based on these different specifications, namely, the contexts,rnand their associated technologies and constraints, we studied the connectivity,rninterference management and the performance criteria. For connectivity criterion,rnwe showthat cognitive radio technology could be able to explore opportunisticallyrnvarious frequencies in order to provide communication channels in eHealthrncontext. Then, for interference management criterion, we propose a managementrnplan that includes strategies to reduce disruptions risks. In addition we havernimplemented one strategy as an example, namely the frequency hopping whichrnis performed when the interference risk on a given channel is high. Finally, wernanalyzed the factors associated with the cognitive radio technology operatingrnmode and that could be the source of likely performance degradation for certainrncategories of medical data. We propose therefore a function that reinforces therncognitive radio Decision-making and Spectrum Sharing modules by controllingrnsome QoS parameters.Keywords: eHealth Systems; Cognitive Radio Networks; Communications Performance (QoS); Interference Management; Permanent Connectivity.

A multi-level generic multi-agent architecture for supervision of collective cyber-physical systemsby Michel Occello, Jean-Paul Jamont, Choukri Ben-Yelles, Thi Thanh Ha Hoang Abstract: Cyber-Physical systems like networked embedded systems or ambient sensors networks are called large scale artificial complex systems. They are difficult to supervise because of their numerous components in interaction relying upon physical devices, their extension and their openness. A multi-scale organization can be a solution to make them more accessible. Multi-agent systems (MAS) are well suited for modeling large complex systems, as multi-agent organizational capabilities allow to introduce multi-level observation. This paper proposes a multi-level multi-agent mechanism based on recursion for supervision and observation of large scale artificial complex systems. It is developed as a free framework that is a decentralized application allowing a truly physically decentralized MAS to communicate with abstract multi-agent layers. As an illustration, the framework is applied to a wireless sensor network supervision system.Keywords: Multi-Agent System; Collective Intelligence; Multi-level; Scalability ; Collective Cyber-Physical System; Wireless sensor network; Monitoring.

Adaptive M-MRC Scheme with Estimation Error over TWDP Fadingby Bhargabjyoti Saikia, Rupaban Subadar Abstract: High speed data requirement among a large group of user is one of the key challenges in wireless communication. To meet this requirement adaptive multi-antenna system (adaptive diversity receiver) is a well known potential solution in wireless system design. Nevertheless, the ideal estimation technique which is considered to optimized the performance of a diversity receiver is difficult to get. Hence, in a practical scenario, the expected system performance of the receiver is considerably degraded. In this paper the Average Bit Error Rate (ABER) and capacity analysis has been studied for an arbitrary branch maximum ratio combiner (MRC) system for different modulation techniques over Two Wave Diffused Power (TWDP) fading channels with error in estimation.Keywords: Estimation Error; Adaptive System; MRC receiver; TWDP fading; ABER; Channel Capacity; Coherent Modulation.

L(d,1)-labellings of generalised Petersen graphsby Fei Deng, Xiaoling Zhong, Zehui Shao Abstract: An interesting graph distance constrained labelling problem can model the frequency channel assignment problem as well as code assignment in computer networks. The frequency assignment problem asks for assigning frequencies to transmitters in a broadcasting network with the aim of avoiding undesired interference. One of the graph theoretical models of The frequency assignment problem is the concept of distance constrained labelling of graphs. Let u and v be vertices of a graph G = (V (G),E(G)) and d(u, v) be the distance between u and v in G. For an integer d ≥ 0, an L(d, 1)-labelling of G is a function f : V (G) → {0, 1, · · · } such that for every u, v ∈ V (G), |f(u) − f(v)| ≥ d if d(u, v) = 1 and |f(u) − f(v)| ≥ 1 if d(u, v) = 2. The span of f is the difference between the largest and the smallest numbers in f(V (G)). The λd,1-number of G is the minimum span over all L(d, 1)-labellings of G. For natural numbers n and k, where n > 2k, a generalised Petersen graph P(n, k) is obtained by letting its vertex set be {u1, u2, · · · , un} ∪ {v1, v2, · · · , vn} and its edge set be the union of uiui+1, uivi, vivi+k over 1 ≤ i ≤ n, where subscripts are reduced modulo n. In this paper, we show the λd,1-numbers of the generalised Petersen graphs P(n, k) for n ≥ 5.Keywords: graph labelling; generalised Petersen graph; code assignment; frequency assignment problem.DOI: 10.1504/IJAACS.2018.10013244

Sleeping scheme based on grey forecast and time division for heterogeneous WSNsby Huiru Cao, Hehua Yan Abstract: The current evaluation models of hierarchical wireless sensor networks (WSNs) are based on some idealistic hypothesis, such as fixed amount of data transmission and electing cluster head mechanism. In order to solve these problems, extend network life of clustering-WSNs by reducing unnecessary monitoring and power consumption, a sleeping scheme based on grey forecast model and time division (GFTD) in cluster-WSNs is proposed. Using grey forecast algorithm and historical records to computing sleep time, this scheme dynamically predicts and adjusts nodes sleep time. Moreover, fixed cluster head strategy and a mechanism of data transmission in time division multiplexing (TDM) mode are presented to reduce the process of cluster head selection and the frequency of the state-switching of nodes. Meantime, the algorithm could ensure the integrity of transmitted information. Simulation results show that the algorithm of GFTD, compared to other existing, exhibit a longer working time with more sleeping time and more residual energy. Lastly, a simple WSN is built up, experimental results show that the relative error of sleep time calculated by the GFTD and the theoretical value is less than 5%.Keywords: wireless sensor network; WSN; sleeping forecast; heterogeneous network; grey forecast model; time division.DOI: 10.1504/IJAACS.2018.10013245

Multi-agent reinforcement learning-based approach for controlling signals through adaptationby Mohammed Tahifa, Jaouad Boumhidi, Ali Yahyaouy Abstract: In this paper, we present a multi-agent reinforcement learning-based approach for controlling traffic signals. The aim is to use a multi-agent system with learning abilities for controlling and optimising traffic lights. We consider in this study the Q-learning algorithm, where the states are computed from average queue length in approaching links. The action space is modelled offline by using different time splits. The adaptation of the considered learning optimal policy through online learning is introduced to deal with the change of the environment. The simulation results show the effectiveness of the proposed adaptive learning algorithm.Keywords: multi-agent systems; reinforcement learning; adaptation; traffic signal control; Q-learning.DOI: 10.1504/IJAACS.2018.10013246

Automatic modulation recognition for DVB-S2 using pairwise support vector machinesby Mohsen Farhang, Ali Ghaleh, Hamid Dehghani Abstract: In this paper, a support vector machine (SVM) pairwise coupling algorithm is developed for classification of satellite communications signals used in second generation of digital video broadcasting via satellite (DVB-S2) standard. DVB-S2 standard adaptively uses one of QPSK, 8PSK, 16APSK, and 32APSK modulations. The proposed method extracts fourth and sixth order cumulants as features from the received signal. The features are given to a SVM pairwise coupling algorithm in which there is one binary SVM for each pair of modulation types. Finally the algorithm selects the modulation type chosen by the maximal number of pairwise SVMs as final decision. SVMs are trained by samples from different modulation types corrupted by Gaussian noise. The simulation results show that the proposed method allows higher recognition rates in comparison with previous methods, especially at low SNRs.Keywords: automatic modulation classification; AMC; pairwise support vector machine; cumulant; digital video broadcasting via satellite; DVB-S2.DOI: 10.1504/IJAACS.2018.10013247

Cognitive fuzzy flow control for wireless routersby Mirjami Jutila, Tapio Frantti Abstract: This paper presents fuzzy set theory-based cognitive control system for IEEE 802.11b wireless local area networks (WLANs). Developed fuzzy weighted queueing (FWQ) method anticipates required changes on weight coefficients with optimal packet sizes for adaptive flow control. Traffic flows are scheduled for prevailing traffic level on WLAN-based router. The algorithm determines the amount of allowed bandwidth for each service class in the outputs of wireless router anticipating the application dependent delay and packet loss rate. It is shown through simulations that the developed FWQ model is also more stable and reacts faster to different traffic states than drop-tail or weighted fair queueing (WFQ) schedulers that were used here as comparative methods. Delay times and packet loss rates of the FWQ algorithm were lower than drop-tail's or WFQ's respective values with different amounts of background traffic.Keywords: quality of service; QoS; queueing; scheduling; packet size control; fuzzy control; expert system; fuzzy weighted queueing; FWQ; weighted fair queueing; WFQ.DOI: 10.1504/IJAACS.2018.10013248

Using program branch probability for the thread parallelisation of branch divergence on the CUDA platformby Hong Yao, Huifang Deng, Caifeng Zou Abstract: Virtualisation environment can bring more flexibility for parallel optimisation. In view of this, we focus on the divergent branch problem within a SIMT architecture, where threads with branch divergence should be serially executed. Existing approaches are normally costly and not so satisfactory in vectorising these threads due to the constraints of private variables. However, on the other hand, these constraints can be released in a virtualised environment, because the private resources can be avoided putting in use directly by applications. For virtualised CUDA platforms, our approach can converge isomorphic threads into same redundant warps to eliminate divergence. We introduce the algorithms for the thread recombination models of binary branches, single branch and multiple branches respectively, and each number of redundant warps can be determined by a program branch probability. Without redesigning hardware needed, we obtained a load balance schema for parallelisation of divergent branch threads.Keywords: GPGPU; SIMT architecture; compute unified device architecture; CUDA; branch divergence; performance optimisation; code structure; program branch probability; PBP; thread recombination; redundant warp; hash table; warp lane.DOI: 10.1504/IJAACS.2018.10013261